Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems
The Wireless Sensor Network (WSN) has emerged as a promising tool for monitoring the physical world, utilizing self-organizing networks of battery-powered wireless sensors that can sense, process and communicate. It can be deployed rapidly and cheaply, thereby enabling large-scale, on-demand monitor...
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my-usim-ddms-12378 |
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uketd_dc |
| institution |
Universiti Sains Islam Malaysia |
| collection |
USIM Institutional Repository |
| language |
English |
| topic |
Wireless sensor networks |
| spellingShingle |
Wireless sensor networks Kalid Abdlkader Marsal Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| description |
The Wireless Sensor Network (WSN) has emerged as a promising tool for monitoring the physical world, utilizing self-organizing networks of battery-powered wireless sensors that can sense, process and communicate. It can be deployed rapidly and cheaply, thereby enabling large-scale, on-demand monitoring and tracking over a wide range of applications. Sensor nodes in such a network usually have limited on-board processing and wireless communication capabilities, and are equipped with batteries prolong the network lifetime. However, if all the sensor nodes simultaneously operated, redundant sensing data, corresponding wireless communication collision and interference will cause much energy to be wasted. How does one cover all the sensing area with the least active nodes so that no blind-point exists and connectivity is kept significant? Coverage becomes a serious problem in large scale sensor networks where hundreds and thousands of nodes are randomly deployed. The coverage problem is one of the most fundamental issues in wireless sensor. Current solutions are based for the most part on node scheduling, the main idea of which is to find the optimal number of active nodes while maintaining coverage and connectivity. The problem in finding the maximal coverage in a sensor network addressed in where coverage is defined as a set of nodes that can completely cover the monitored are, and a centralized solution to this problem is proposed. Several algorithms aim to find a close-to-optimal solution based on local information. In this work, a new method for controlling WSN main parameters (such as energy consumption, bandwidth, signal strength and coverage) using single fitness function proposed, developed and tested. In order to complete this research a network simulates is developed main Microsoft visual C# and a few experiments are done on the simulator. In future research, more and more work will be focused on distributed and localized solutions for practical deployment by simulation wireless sensor networks. In this simulation can be run either be reset with a new seed or with the previous seed for replay. |
| format |
Thesis |
| author |
Kalid Abdlkader Marsal |
| author_facet |
Kalid Abdlkader Marsal |
| author_sort |
Kalid Abdlkader Marsal |
| title |
Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| title_short |
Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| title_full |
Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| title_fullStr |
Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| title_full_unstemmed |
Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| title_sort |
single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems |
| granting_institution |
Universiti Sains Islam Malaysia |
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1812444912431398912 |
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my-usim-ddms-123782024-05-29T20:30:29Z Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems Kalid Abdlkader Marsal The Wireless Sensor Network (WSN) has emerged as a promising tool for monitoring the physical world, utilizing self-organizing networks of battery-powered wireless sensors that can sense, process and communicate. It can be deployed rapidly and cheaply, thereby enabling large-scale, on-demand monitoring and tracking over a wide range of applications. Sensor nodes in such a network usually have limited on-board processing and wireless communication capabilities, and are equipped with batteries prolong the network lifetime. However, if all the sensor nodes simultaneously operated, redundant sensing data, corresponding wireless communication collision and interference will cause much energy to be wasted. How does one cover all the sensing area with the least active nodes so that no blind-point exists and connectivity is kept significant? Coverage becomes a serious problem in large scale sensor networks where hundreds and thousands of nodes are randomly deployed. The coverage problem is one of the most fundamental issues in wireless sensor. Current solutions are based for the most part on node scheduling, the main idea of which is to find the optimal number of active nodes while maintaining coverage and connectivity. The problem in finding the maximal coverage in a sensor network addressed in where coverage is defined as a set of nodes that can completely cover the monitored are, and a centralized solution to this problem is proposed. Several algorithms aim to find a close-to-optimal solution based on local information. In this work, a new method for controlling WSN main parameters (such as energy consumption, bandwidth, signal strength and coverage) using single fitness function proposed, developed and tested. In order to complete this research a network simulates is developed main Microsoft visual C# and a few experiments are done on the simulator. In future research, more and more work will be focused on distributed and localized solutions for practical deployment by simulation wireless sensor networks. In this simulation can be run either be reset with a new seed or with the previous seed for replay. Universiti Sains Islam Malaysia 2015 Thesis en https://oarep.usim.edu.my/handle/123456789/12378 https://oarep.usim.edu.my/bitstreams/071eeabc-9047-4ee2-a9bb-2e1c18083da4/download 8a4605be74aa9ea9d79846c1fba20a33 https://oarep.usim.edu.my/bitstreams/8ad23e8f-bfd0-4daa-867a-7f305cbb985a/download 024c3b205df59df15e4671a9ea145598 https://oarep.usim.edu.my/bitstreams/ef9744f7-9a1c-482e-9fdb-646597a70199/download ebc9ba47d3547eb295efc8c02b3b112b https://oarep.usim.edu.my/bitstreams/3981ab06-d585-4ea6-bb5a-4999cf7d06cd/download 879a2abb20001a0dc03fc120497a4f76 https://oarep.usim.edu.my/bitstreams/3daa5de7-d7ba-4427-92b9-fb790707da29/download 27315cec4ac58171701e673b672c5b37 https://oarep.usim.edu.my/bitstreams/b2bc4b62-09fe-4bc6-844c-4b19038ae203/download 34db36d58b498ee384af1d2598d34bdd https://oarep.usim.edu.my/bitstreams/59dd5c4e-addf-435e-93a5-713ed930ac41/download 9b173d9885890657c8436bada6b0276a https://oarep.usim.edu.my/bitstreams/839622f1-9b2f-480e-96b2-e04e0f5f36f3/download b32afed0910a6773939bbdcb56469141 https://oarep.usim.edu.my/bitstreams/5709d34d-27ec-492c-8bf9-0dc68c2afd4a/download 9d31dc129c11081dc7f5f11ff07bb8e0 https://oarep.usim.edu.my/bitstreams/02edcdf4-03b9-4d78-a61d-96c8e1b4fcc0/download 68b329da9893e34099c7d8ad5cb9c940 https://oarep.usim.edu.my/bitstreams/df0f5567-19e7-48e7-ac4c-c3252b163a81/download 76ce487d9e90ad2e3e31003253525e61 https://oarep.usim.edu.my/bitstreams/02de0eee-43fb-4fb6-9c47-bd6f51d3e4e9/download b308b7fe5c1c2bbdc0cb686d451b84aa https://oarep.usim.edu.my/bitstreams/67f7bb82-9d9b-4682-92ef-9c43abb10d0a/download 884e307a96265ab0e1bf7bcc1f89c892 https://oarep.usim.edu.my/bitstreams/dea6af66-5799-4b87-942a-95676f812be9/download f8e02f37010c5a38b4b7747b169de886 https://oarep.usim.edu.my/bitstreams/cb4ba96d-7b31-408f-a531-1ff87739e52b/download 2c6eb67c8897d916ae47524b1a844d3f https://oarep.usim.edu.my/bitstreams/f15d1bf6-1510-4d4d-95c5-927639916dd6/download ff4c8ff01d544500ea4bfea43e6108c1 https://oarep.usim.edu.my/bitstreams/154b0c71-7c13-4c12-bb4f-7b2b1161c34b/download 2c6eb67c8897d916ae47524b1a844d3f Wireless sensor networks |